A novel fast scene classification method via DCT

Scene classification is a hot problem in the computer vision. In this paper, a novel rapid scene classification method is proposed based on the discrete cosine transform (DCT) domain. Firstly, we divided the whole image into several areas of the same size without repetition, do DCT transform with th...

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Bibliographic Details
Published in2014 7th International Congress on Image and Signal Processing pp. 650 - 654
Main Authors Ce Li, Ming Li, Meili Xiao, Zhijia Hu, Xiuxun Miao, Zhengrong Pan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2014
Subjects
Accuracy
Buildings
compressed domain
DCT
directionality
Discrete cosine transforms
Feature extraction
multi-resolution
scene classification
Support vector machine classification
Vectors
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Summary:Scene classification is a hot problem in the computer vision. In this paper, a novel rapid scene classification method is proposed based on the discrete cosine transform (DCT) domain. Firstly, we divided the whole image into several areas of the same size without repetition, do DCT transform with the size of the B * B in each separate sub image area divided above. Secondly, scanning AC coefficients in each DCT block by three ways, modeling based on the correlation between AC coefficients in DCT block for extracting the feature vectors. Finally, with the feature vectors obtained previously, using one-vs-all Support Vector Machine train classifiers. Experimental results show that the proposed method is effective in image classification.
DOI:10.1109/CISP.2014.7003859